On the fuzzy comprehensive evaluation method in the tourist resort apartment investment decisions in the application _ to write papers Network

Write papers network: [Abstract] vacation apartment is a special type of Tourism real estate, its good momentum of Development to attract more and more attention from investors this paper using the Delphi method and AHP to establish vacation apartment Investment making the evaluation index system, and determine its weight, and finally the use of fuzzy comprehensive evaluation method to establish vacation apartment Investment decision evaluation model and conduct empirical Research.

[Keywords] vacation apartment Investment decisions AHP fuzzy comprehensive evaluation method

Fuzzy comprehensive evaluation (fuzzy comprehensive evaluation method) is based on fuzzy comprehensive evaluation method, automatic control experts in the United States Chad (LAZadeh) proposed in 1965, Professor of fuzzy set theory based on the concept evolved. The fuzzy comprehensive evaluation method based on the degree of membership theory to qualitative evaluation into quantitative evaluation, which uses fuzzy Mathematics is affected by many factors or things that make an overall evaluation of the object it has a clear result, the characteristics of strong systemic , can be solved vague, difficult to quantify the problem, often applied to solve a variety of non-deterministic and complex issues. Fuzzy comprehensive evaluation method for the application of Research mainly Lu Ying (2007 overall competitiveness of enterprises assessment,
Zhang Yuan Yuan (2010 evaluation of bank customer satisfaction, Wang Qiurong (2010) for college tutor performance evaluation in real estate, fuzzy comprehensive evaluation method has many applications, such as Zhu Yong (2004, Zhang (2007, Li Xu down ( 2008 and so try to use fuzzy comprehensive evaluation method for real estate Investment risk, Investment decision-making on the theoretical and applied Research.

Resort Apartment (Tourism Vacation Rentals) real estate as a special type of Tourism, its home-like experience, personalized custom services, by the visitors alike, more and more visitors to its tourist resort holiday apartments accommodation options. This article from the perspective of investors, analyzes the characteristics of vacation condo market, the use of fuzzy comprehensive evaluation method to build their Investment decision-making evaluation model, and applied empirical Research.

A vacation apartment Investment decision-making evaluation index system
Tourism, real estate and residential real estate in general is not exactly the same Investment decisions because, Tourism, real estate and real estate and tourism Development as a whole, to meet function on the basis of residential and tourist resort is also involved in related services. Holiday apartment is a real estate tour species of special type, with hotel-style services, apartment-style management features, which makes its Investment decisions investors need a multi-disciplinary considerations. Currently, the major influencing factors for the following classification criteria: (1 Classification by function of time, can be divided into historical factors, the current factors, post-factors, (2 classified by impact angle, can be divided into factors affecting supply and demand factors, such as competitive factors, (3 categories according to the scope, background factors can be divided into macro, meso and regional factors, micro-project factors [4] In this paper, based on the characteristics of vacation apartments, combined with the present findings, coupled with on the author's point of view, the resort is divided into factors affecting Investment decisions apartment location factors, economic factors, policy factors, social factors, industry factors, post operating factors, such as six-level indicators, geographical location, environment, transportation, infrastructure and other 22 secondary indicators.

On this basis, combined with expert opinion (Delphi method to determine the selection of indicators, a total of 12 questionnaires (survey was conducted in Sanya Orient Ward Investment Co., Ltd., vacation apartments for investment decision-making factors in the 22 secondary indicators vacation apartment and the correlation between views of decision-making recovery, and the filter, try to build a tourist resort apartment investment decision-making evaluation system (see Figure 1.

Second, the vacation apartment investment decisions determine the weights of evaluation indicators
In Figure 1, based on questionnaire design (a little survey of experts, by experts score the indicators at all levels of the weight required to build each level indicators to determine the matrix AB, B1-C, B2-C, B3-C, B4- C, B5-C, B6-C, and the criteria for sorting through the level and consistency of a single test and the total level of order and consistency test, to determine the judge set the matrix of eigenvectors.

To simplify the calculation process, the level of single-level analysis criteria and the total level of consistency checking and sorting and consistency check of calculation using MATLAB software programming (programming code slightly, to determine the matrix were calculated for each feature vector set and the maximum eigenvalue and the consistency test, the level of index weight are as follows:
A = (0.2725,0.0570,0.3768,0.0379, 0.1540,0.1019)
B1 = (0.5290,0.2339,0.0866,0.1505
B2 = (0.0569,0.5579,0.2633,0.1219
B3 = (0.2500,0.7500
B4 = (0.5777,0.2378,0.1289,0.0557
B5 = (0.0417,0.2011,0.0779,0.5083,0.1710
B6 = (0.8333,0.1667
Third, vacation apartment investment decisions to build fuzzy comprehensive evaluation model
1 to establish an evaluation factor set U
Evaluation factors set is generally represented by U, that is, its set for the evaluation of sub-elements: Links to free download http://www.hi138.com
(2) the establishment of a collection of weights
The main level of each factor is usually not the same, in order to reflect the importance of various factors on the various factors to give the appropriate weight, the weight set is
3 Rank collection to determine
Rank V to general use, ie.

4. Establish fuzzy evaluation matrix
Level indicators which represent the child elements of the j-level evaluation of the degree of membership (i = 1,2 ,..., m; j = 1,2 ,..., n).

5 fuzzy matrix operation and received the results
(1 single factor fuzzy evaluation
Level indicators for each sub-factor evaluation matrix for the fuzzy matrix operations, has been the main factor in the evaluation of grade level targets set under the vector by, we get:
(2) fuzzy comprehensive evaluation
Grade level indicators for evaluating the target set under the vector can be obtained:
Among them, the level of U for the evaluation of the degree of membership, according to the judge the size of membership level, to determine the maximum level that is a target level.

Fourth, the case studies - Sanya Azur holiday apartment investment decision-making evaluation
Azur holiday apartment project located in the famous tourist scenic Sanya - Sanya Bay coast, near Sanya, Sanya is the axis of Development of urban space in prime locations. The project area is located beside the beautiful Coconut Dream Corridor, wear through the garden gate area less than 50 meters is a natural bathing beach, away from Sanya Phoenix International Airport about 11 km from the bus station and only 3 km from the city Wanfulong Supermarket, Wang Hao supermarket just 10 minutes, the traffic is very convenient Sanya the future of tourism, leisure, vacation, and health-in-one luxury holiday apartments.

1 investment decisions Rank
According to experts, the establishment of the project scoring evaluation of each grade-level indicators, evaluation of location factors, the following table-type level (data omitted other factors:
(2) evaluation based on the evaluation given language level, get fuzzy Information, the establishment of the corresponding fuzzy matrix were:
3. Find the sub-factors corresponding to the level set under the vector evaluation by Part 2 of this level of analysis to seek indicators of various levels of weight and available (for all levels of weight):
4 obtain the target level set under the level of the corresponding evaluation vector B, that is, Sanya Azur holiday apartment comprehensive evaluation.

This article builds fuzzy model, the tourist resort apartments set into the evaluation of investment decisions V = {V1, V2, V3, V4} = {A, B, C, D}, excellent, good, fair, poor grades four as follows:
Class A: The investment value of outstanding holiday apartment ideal for investment, virtually risk-free, while at A-level evaluation of the project, its evaluation set V = {1,0,0,0}.

Class B: The value of a good holiday apartment investment projects for investment, little risk, when the project evaluation in Class B, its evaluation set V = {0,1,0,0}.

Class C: The holiday apartment investment value in general, more suitable for investment, risk, when the C-level evaluation of the project, its evaluation set V = {0,0,1,0}.

Class D: The difference between the value of investment projects, holiday apartment, is not suitable for investment, the risk is very large; when the project evaluation in the D grade, the evaluation set V = {0,0,0,1}.

Using Euclid close degree of B for processing:
According to the theory of fuzzy Mathematics elective principle we can see past the target level corresponding to the evaluation grade of membership with the V2 vector closest to that Sanya Azur holiday apartment comprehensive evaluation of Class B, the value of a good investment.

V. Conclusion
Vacation apartment investment decision evaluation is a comprehensive, complex analysis, the factors involved in all aspects because of my limited ability, coupled with the concept of perfect vacation apartments, as well as Information, data, case collection was incomplete, so there is this the inadequacies, need further study for further Research, I propose the following: (1) This vacation apartment for the selection of factors, the consideration was inadequate for one aspect in the selection of indicators needs further standardize and improve; (2 this case study, due to the difficulties of data collection, only consider the operation of the project before the investment decision-making behavior, while the latter part of the actual operation of the project and investment decision-making model of the test, comparing the actual needs further test.


References:
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[2] Zhang, Zhu Xinhua fuzzy comprehensive evaluation method in the real estate investment decision-making applications [J]. Information Development & Economy 2006, (23:158
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[4] Cui Feng. Commercial real estate market positioning evaluation index system architecture [D]. Chongqing: Chongqing University, 2005:17 - 20.

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